Neural basis of the set-size effect in frontal eye field: timing of attention during visual search

Inversion of pop-out for a distracting feature dimension in monkey visual cortex

During visual search, it is important to reduce the interference of distracting objects in the scene. The neuronal responses elicited by the search target stimulus are typically enhanced. However, it is equally important to suppress the representations of distracting stimuli, especially if they are salient and capture attention. We trained monkeys to make an eye movement to a unique "pop-out" shape stimulus among an array of distracting stimuli. One of these distractors had a salient color that varied across trials and differed from the color of the other stimuli, causing it to also pop-out. The monkeys were able to select the pop-out shape target with high accuracy and actively avoided the pop-out color distractor. This behavioral pattern was reflected in the activity of neurons in area V4. Responses to the shape targets were enhanced, while the activity evoked by the pop-out color distractor was only briefly enhanced, directly followed by a sustained period of pronounced suppression. These behavioral and neuronal results demonstrate a cortical selection mechanism that rapidly inverts a pop-out signal to "pop-in" for an entire feature dimension thereby facilitating goal-directed visual search in the presence of salient distractors.

Frontal eye fields in macaque monkeys: prefrontal and premotor contributions to visually guided saccades

Neuronal spiking was sampled from the frontal eye field (FEF) and from the rostral part of area 6 that reaches to the superior limb of the arcuate sulcus, dorsal to the arcuate spur when present (F2vr) in macaque monkeys performing memory-guided saccades and visually guided saccades for visual search. Neuronal spiking modulation in F2vr resembled that in FEF in many but not all respects. A new consensus clustering algorithm of neuronal modulation patterns revealed that F2vr and FEF contain a greater variety of modulation patterns than previously reported. The areas differ in the proportions of visuomotor neuron types, the proportions of neurons discriminating a target from distractors during visual search, and the consistency of modulation patterns across tasks. However, between F2vr and FEF we found no difference in the magnitude of delay period activity, the timing of the peak discharge rate relative to saccades, or the time of search target selection. The observed similarities and differences between the 2 cortical regions contribute to other work establishing the organization of eye fields in the frontal lobe and may help explain why FEF in monkeys is identified within granular prefrontal area 8 but in humans is identified within agranular premotor area 6.

Urgent Decision Making: Resolving Visuomotor Interactions at High Temporal Resolution

Measuring when exactly perceptual decisions are made is crucial for defining how the activation of specific neurons contributes to behavior. However, in traditional, nonurgent visuomotor tasks, the uncertainty of this temporal measurement is very large. This is a problem not only for delimiting the capacity of perception, but also for correctly interpreting the functional roles ascribed to choice-related neuronal responses. In this article, we review psychophysical, neurophysiological, and modeling work based on urgent visuomotor tasks in which this temporal uncertainty can be effectively overcome. The cornerstone of this work is a novel behavioral metric that describes the evolution of the subject's perceptual judgment moment by moment, allowing us to resolve numerous perceptual events that unfold within a few tens of milliseconds. In this framework, the neural distinction between perceptual evaluation and motor selection processes becomes particularly clear, as the conclusion of one is not contingent on that of the other. Expected final online publication date for the Annual Review of Vision Science, Volume 7 is September 2021. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Change point detection with multiple alternatives reveals parallel evaluation of the same stream of evidence along distinct timescales

In order to behave appropriately in a rapidly changing world, individuals must be able to detect when changes occur in that environment. However, at any given moment, there are a multitude of potential changes of behavioral significance that could occur. Here we investigate how knowledge about the space of possible changes affects human change point detection. We used a stochastic auditory change point detection task that allowed model-free and model-based characterization of the decision process people employ. We found that subjects can simultaneously apply distinct timescales of evidence evaluation to the same stream of evidence when there are multiple types of changes possible. Informative cues that specified the nature of the change led to improved accuracy for change point detection through mechanisms involving both the timescales of evidence evaluation and adjustments of decision bounds. These results establish three important capacities of information processing for decision making that any proposed neural mechanism of evidence evaluation must be able to support: the ability to simultaneously employ multiple timescales of evidence evaluation, the ability to rapidly adjust those timescales, and the ability to modify the amount of information required to make a decision in the context of flexible timescales.

The functional roles of neural remapping in cortex

Remapping is a property of some cortical and subcortical neurons that update their responses around the time of an eye movement to account for the shift of stimuli on the retina due to the saccade. Physiologically, remapping is traditionally tested by briefly presenting a single stimulus around the time of the saccade and looking at the onset of the response and the locations in space to which the neuron is responsive. Here we suggest that a better way to understand the functional role of remapping is to look at the time at which the neural signal emerges when saccades are made across a stable scene. Based on data obtained using this approach, we suggest that remapping in the lateral intraparietal area is sufficient to play a role in maintaining visual stability across saccades, whereas in the frontal eye field, remapped activity carries information that affects future saccadic choices and, in a separate subset of neurons, is used to maintain a map of locations in the scene that have been previously fixated.

Mechanisms of competitive selection: A canonical neural circuit framework

Competitive selection, the transformation of multiple competing sensory inputs and internal states into a unitary choice, is a fundamental component of animal behavior. Selection behaviors have been studied under several intersecting umbrellas including decision-making, action selection, perceptual categorization, and attentional selection. Neural correlates of these behaviors and computational models have been investigated extensively. However, specific, identifiable neural circuit mechanisms underlying the implementation of selection remain elusive. Here, we employ a first principles approach to map competitive selection explicitly onto neural circuit elements. We decompose selection into six computational primitives, identify demands that their execution places on neural circuit design, and propose a canonical neural circuit framework. The resulting framework has several links to neural literature, indicating its biological feasibility, and has several common elements with prominent computational models, suggesting its generality. We propose that this framework can help catalyze experimental discovery of the neural circuit underpinnings of competitive selection.

Principles of tactile search over the body

Although we routinely experience complex tactile patterns over our entire body, how we selectively experience multisite touch over our bodies remains poorly understood. Here, we characterized tactile search behavior over the full body using a tactile analog of the classic visual search task. On each trial, participants judged whether a target stimulus (e.g., 10-Hz vibration) was present or absent anywhere on the body. When present, the target stimulus could occur alone or simultaneously with distractor stimuli (e.g., 30-Hz vibrations) on other body locations. We systematically varied the number and spatial configurations of the distractors as well as the target and distractor frequencies and measured the impact of these factors on tactile search response times. First, we found that response times were faster on target-present trials compared with target-absent trials. Second, response times increased with the number of stimulated sites, suggesting a serial search process. Third, search performance differed depending on stimulus frequencies. This frequency-dependent behavior may be related to perceptual grouping effects based on timing cues. We constructed linear models to explore how the locations of the target and distractor cues influenced tactile search behavior. Our modeling results reveal that, in isolation, cues on the index fingers make relatively greater contributions to search performance compared with stimulation experienced on other body sites. Additionally, costimulation of sites within the same limb or simply on the same body side preferentially influence search behavior. Our collective findings identify some principles of attentional search that are common to vision and touch, but others that highlight key differences that may be unique to body-based spatial perception.NEW & NOTEWORTHY Little is known about how we selectively experience multisite touch patterns over the body. Using a tactile analog of the classic visual target search paradigm, we show that tactile search behavior for flutter cues is generally consistent with a serial search process. Modeling results reveal the preferential contributions of index finger stimulation and two-site stimulus interactions involving ipsilateral patterns and within-limb patterns. Our results offer initial evidence for spatial and temporal principles underlying tactile search behavior over the body.

Activity in LIP, But not V4, Matches Performance When Attention is Spread

The enhancement of neuronal responses in many visual areas while animals perform spatial attention tasks has widely been thought to be the neural correlate of visual attention, but it is unclear whether the presence or absence of this modulation contributes to our striking inability to notice changes in change blindness examples. We asked whether neuronal responses in visual area V4 and the lateral intraparietal area (LIP) in posterior parietal cortex could explain the limited ability of subjects to attend multiple items in a display. We trained animals to perform a change detection task in which they had to compare 2 arrays of stimuli separated briefly in time and found that each animal's performance decreased as function of set-size. Neuronal discriminability in V4 was consistent across set-sizes, but decreased for higher set-sizes in LIP. The introduction of a reward bias produced attentional enhancement in V4, but this could not explain the vast improvement in performance, whereas the enhancement in LIP responses could. We suggest that behavioral set-size effects and the marked improvement in performance with focused attention may not be related to response enhancement in V4 but, instead, may occur in or on the way to LIP.

Selective Influence and Sequential Operations: A Research Strategy for Visual Search

We discuss the problem of elucidating mechanisms of visual search. We begin by considering the history, logic, and methods of relating behavioral or cognitive processes with neural processes. We then survey briefly the cognitive neurophysiology of visual search and essential aspects of the neural circuitry supporting this capacity. We introduce conceptually and empirically a powerful but underutilized experimental approach to dissect the cognitive processes supporting performance of a visual search task with factorial manipulations of singleton-distractor identifiability and stimulus-response cue discriminability. We show that systems factorial technology can distinguish processing architectures from the performance of macaque monkeys. This demonstration offers new opportunities to distinguish neural mechanisms through selective manipulation of visual encoding, search selection, rule encoding, and stimulus-response mapping.

The Neurodynamic Decision Variable in Human Multi-alternative Perceptual Choice

The neural dynamics underpinning binary perceptual decisions and their transformation into actions are well studied, but real-world decisions typically offer more than two response alternatives. How does decision-related evidence accumulation dynamically influence multiple action representations in humans? The heightened conservatism required in multiple compared with binary choice scenarios suggests a mechanism that compensates for increased uncertainty when multiple choices are present by suppressing baseline activity. Here, we tracked action representations using corticospinal excitability during four- and two-choice perceptual decisions and modeled them using a sequential sampling framework. We found that the predictions made by leaky competing accumulator models to accommodate multiple choices (i.e., reduced baseline activity to compensate increased uncertainty) were borne out by dynamic changes in human action representations. This suggests a direct and continuous influence of interacting evidence accumulators, each favoring a different decision alternative, on downstream corticospinal excitability during complex choice.

Functional Categories of Visuomotor Neurons in Macaque Frontal Eye Field

Frontal eye field (FEF) in macaque monkeys contributes to visual attention, visual-motor transformations and production of eye movements. Traditionally, neurons in FEF have been classified by the magnitude of increased discharge rates following visual stimulus presentation, during a waiting period, and associated with eye movement production. However, considerable heterogeneity remains within the traditional visual, visuomovement, and movement categories. Cluster analysis is a data-driven method of identifying self-segregating groups within a dataset. Because many cluster analysis techniques exist and outcomes vary with analysis assumptions, consensus clustering aggregates over multiple analyses, identifying robust groups. To describe more comprehensively the neuronal composition of FEF, we applied a consensus clustering technique for unsupervised categorization of patterns of spike rate modulation measured during a memory-guided saccade task. We report 10 functional categories, expanding on the traditional 3 categories. Categories were distinguished by latency, magnitude, and sign of visual response; the presence of sustained activity; and the dynamics, magnitude and sign of saccade-related modulation. Consensus clustering can include other metrics and can be applied to datasets from other brain regions to provide better information guiding microcircuit models of cortical function.

Having More Choices Changes How Human Observers Weight Stable Sensory Evidence

Decision-making becomes slower when more choices are available. Existing models attribute this slowing to poor sensory processing, to attenuated rates of sensory evidence accumulation, or to increases in the amount of evidence required before committing to a decision (a higher decision threshold). However, studies have not isolated the effects of having more choices on sensory and decision-related processes from changes in task difficulty and divided attention. Here, we controlled task difficulty while independently manipulating the distribution of attention and the number of choices available to male and female human observers. We used EEG to measure steady-state visually evoked potentials (SSVEPs) and a frontal late positive deflection (LPD), EEG markers of sensory and postsensory decision-related processes, respectively. We found that dividing attention decreased SSVEP and LPD amplitudes, consistent with dampened sensory responses and slower rates of evidence accumulation, respectively. In contrast, having more choices did not alter SSVEP amplitude and led to a larger LPD. These results suggest that having more options largely spares early sensory processing and slows down decision-making via a selective increase in decision thresholds.SIGNIFICANCE STATEMENT When more choices are available, decision-making becomes slower. We tested whether this phenomenon is due to poor sensory processing, to reduced rates of evidence accumulation, or to increases in the amount of evidence required before committing to a decision (a higher decision threshold). We measured choice modulations of sensory and decision-related neural responses using EEG. We also minimized potential confounds from changes in the distribution of attention and task difficulty, which often covary with having more choices. Dividing attention reduced the activity levels of both sensory and decision-related responses. However, having more choices did not change sensory processing and led to larger decision-related responses. These results suggest that having more choices spares sensory processing and selectively increases decision thresholds.

A probabilistic, distributed, recursive mechanism for decision-making in the brain

Decision formation recruits many brain regions, but the procedure they jointly execute is unknown. Here we characterize its essential composition, using as a framework a novel recursive Bayesian algorithm that makes decisions based on spike-trains with the statistics of those in sensory cortex (MT). Using it to simulate the random-dot-motion task, we demonstrate it quantitatively replicates the choice behaviour of monkeys, whilst predicting losses of otherwise usable information from MT. Its architecture maps to the recurrent cortico-basal-ganglia-thalamo-cortical loops, whose components are all implicated in decision-making. We show that the dynamics of its mapped computations match those of neural activity in the sensorimotor cortex and striatum during decisions, and forecast those of basal ganglia output and thalamus. This also predicts which aspects of neural dynamics are and are not part of inference. Our single-equation algorithm is probabilistic, distributed, recursive, and parallel. Its success at capturing anatomy, behaviour, and electrophysiology suggests that the mechanism implemented by the brain has these same characteristics.

Decision-making is central to cognition. Abnormally-formed decisions characterize disorders like over-eating, Parkinson’s and Huntington’s diseases, OCD, addiction, and compulsive gambling. Yet, a unified account of decision-making has, hitherto, remained elusive. Here we show the essential composition of the brain’s decision mechanism by matching experimental data from monkeys making decisions, to the knowable function of a novel statistical inference algorithm. Our algorithm maps onto the large-scale architecture of decision circuits in the primate brain, replicating the monkeys’ choice behaviour and the dynamics of the neural activity that accompany it. Validated in this way, our algorithm establishes a basic framework for understanding the mechanistic ingredients of decision-making in the brain, and thereby, a basic platform for understanding how pathologies arise from abnormal function.

Integrating Brain and Biomechanical Models-A New Paradigm for Understanding Neuro-muscular Control

To date, realistic models of how the central nervous system governs behavior have been restricted in scope to the brain, brainstem or spinal column, as if these existed as disembodied organs. Further, the model is often exercised in relation to an in vivo physiological experiment with input comprising an impulse, a periodic signal or constant activation, and output as a pattern of neural activity in one or more neural populations. Any link to behavior is inferred only indirectly via these activity patterns. We argue that to discover the principles of operation of neural systems, it is necessary to express their behavior in terms of physical movements of a realistic motor system, and to supply inputs that mimic sensory experience. To do this with confidence, we must connect our brain models to neuro-muscular models and provide relevant visual and proprioceptive feedback signals, thereby closing the loop of the simulation. This paper describes an effort to develop just such an integrated brain and biomechanical system using a number of pre-existing models. It describes a model of the saccadic oculomotor system incorporating a neuromuscular model of the eye and its six extraocular muscles. The position of the eye determines how illumination of a retinotopic input population projects information about the location of a saccade target into the system. A pre-existing saccadic burst generator model was incorporated into the system, which generated motoneuron activity patterns suitable for driving the biomechanical eye. The model was demonstrated to make accurate saccades to a target luminance under a set of environmental constraints. Challenges encountered in the development of this model showed the importance of this integrated modeling approach. Thus, we exposed shortcomings in individual model components which were only apparent when these were supplied with the more plausible inputs available in a closed loop design. Consequently we were able to suggest missing functionality which the system would require to reproduce more realistic behavior. The construction of such closed-loop animal models constitutes a new paradigm of computational neurobehavior and promises a more thoroughgoing approach to our understanding of the brain's function as a controller for movement and behavior.

Concurrent deployment of visual attention and response selection bottleneck in a dual-task: Electrophysiological and behavioural evidence

Visual attention and response selection are limited in capacity. Here, we investigated whether visual attention requires the same bottleneck mechanism as response selection in a dual-task of the psychological refractory period (PRP) paradigm. The dual-task consisted of an auditory two-choice discrimination Task 1 and a conjunction search Task 2, which were presented at variable temporal intervals (stimulus onset asynchrony, SOA). In conjunction search, visual attention is required to select items and to bind their features resulting in a serial search process around the items in the search display (i.e., set size). We measured the reaction time of the visual search task (RT2) and the N2pc, an event-related potential (ERP), which reflects lateralized visual attention processes. If the response selection processes in Task 1 influence the visual attention processes in Task 2, N2pc latency and amplitude would be delayed and attenuated at short SOA compared to long SOA. The results, however, showed that latency and amplitude were independent of SOA, indicating that visual attention was concurrently deployed to response selection. Moreover, the RT2 analysis revealed an underadditive interaction of SOA and set size. We concluded that visual attention does not require the same bottleneck mechanism as response selection in dual-tasks.

Working Memory and Decision-Making in a Frontoparietal Circuit Model

Working memory (WM) and decision-making (DM) are fundamental cognitive functions involving a distributed interacting network of brain areas, with the posterior parietal cortex (PPC) and prefrontal cortex (PFC) at the core. However, the shared and distinct roles of these areas and the nature of their coordination in cognitive function remain poorly understood. Biophysically based computational models of cortical circuits have provided insights into the mechanisms supporting these functions, yet they have primarily focused on the local microcircuit level, raising questions about the principles for distributed cognitive computation in multiregional networks. To examine these issues, we developed a distributed circuit model of two reciprocally interacting modules representing PPC and PFC circuits. The circuit architecture includes hierarchical differences in local recurrent structure and implements reciprocal long-range projections. This parsimonious model captures a range of behavioral and neuronal features of frontoparietal circuits across multiple WM and DM paradigms. In the context of WM, both areas exhibit persistent activity, but, in response to intervening distractors, PPC transiently encodes distractors while PFC filters distractors and supports WM robustness. With regard to DM, the PPC module generates graded representations of accumulated evidence supporting target selection, while the PFC module generates more categorical responses related to action or choice. These findings suggest computational principles for distributed, hierarchical processing in cortex during cognitive function and provide a framework for extension to multiregional models.SIGNIFICANCE STATEMENT Working memory and decision-making are fundamental "building blocks" of cognition, and deficits in these functions are associated with neuropsychiatric disorders such as schizophrenia. These cognitive functions engage distributed networks with prefrontal cortex (PFC) and posterior parietal cortex (PPC) at the core. It is not clear, however, what the contributions of PPC and PFC are in light of the computations that subserve working memory and decision-making. We constructed a biophysical model of a reciprocally connected frontoparietal circuit that revealed shared and distinct functions for the PFC and PPC across working memory and decision-making tasks. Our parsimonious model connects circuit-level properties to cognitive functions and suggests novel design principles beyond those of local circuits for cognitive processing in multiregional brain networks.

Model-based cognitive neuroscience

This special issue explores the growing intersection between mathematical psychology and cognitive neuroscience. Mathematical psychology, and cognitive modeling more generally, has a rich history of formalizing and testing hypotheses about cognitive mechanisms within a mathematical and computational language, making exquisite predictions of how people perceive, learn, remember, and decide. Cognitive neuroscience aims to identify neural mechanisms associated with key aspects of cognition using techniques like neurophysiology, electrophysiology, and structural and functional brain imaging. These two come together in a powerful new approach called model-based cognitive neuroscience, which can both inform cognitive modeling and help to interpret neural measures. Cognitive models decompose complex behavior into representations and processes and these latent model states can be used to explain the modulation of brain states under different experimental conditions. Reciprocally, neural measures provide data that help constrain cognitive models and adjudicate between competing cognitive models that make similar predictions about behavior. As examples, brain measures are related to cognitive model parameters fitted to individual participant data, measures of brain dynamics are related to measures of model dynamics, model parameters are constrained by neural measures, model parameters or model states are used in statistical analyses of neural data, or neural and behavioral data are analyzed jointly within a hierarchical modeling framework. We provide an introduction to the field of model-based cognitive neuroscience and to the articles contained within this special issue.

Object-finding skill created by repeated reward experience

For most animals, survival depends on rapid detection of rewarding objects, but search for an object surrounded by many others is known to be difficult and time consuming. However, there is neuronal evidence for robust and rapid differentiation of objects based on their reward history in primates (Hikosaka, Kim, Yasuda, & Yamamoto, 2014). We hypothesized that such robust coding should support efficient search for high-value objects, similar to a pop-out mechanism. To test this hypothesis, we let subjects (n = 4, macaque monkeys) view a large number of complex objects with consistently biased rewards with variable training durations (1, 5, or 30 + days). Following training, subjects searched for a high-value object (Good) among a variable number of low-value objects (Bad). Consistent with our hypothesis, we found that Good objects were accurately and quickly targeted, often by a single and direct saccade with a very short latency (<200 ms). The dependence of search times on display size reduced significantly with longer reward training, giving rise to a more efficient search (40 ms/item to 16 ms/item). This object-finding skill showed a large capacity for value-biased objects and was maintained in the long-term memory with no interference from reward learning with other objects. Such object-finding skill, and in particular its large capacity and long term retention, would be crucial for maximizing rewards and biological fitness throughout life where many objects are experienced continuously and/or intermittently.

Learning a New Selection Rule in Visual and Frontal Cortex

How do you make a decision if you do not know the rules of the game? Models of sensory decision-making suggest that choices are slow if evidence is weak, but they may only apply if the subject knows the task rules. Here, we asked how the learning of a new rule influences neuronal activity in the visual (area V1) and frontal cortex (area FEF) of monkeys. We devised a new icon-selection task. On each day, the monkeys saw 2 new icons (small pictures) and learned which one was relevant. We rewarded eye movements to a saccade target connected to the relevant icon with a curve. Neurons in visual and frontal cortex coded the monkey's choice, because the representation of the selected curve was enhanced. Learning delayed the neuronal selection signals and we uncovered the cause of this delay in V1, where learning to select the relevant icon caused an early suppression of surrounding image elements. These results demonstrate that the learning of a new rule causes a transition from fast and random decisions to a more considerate strategy that takes additional time and they reveal the contribution of visual and frontal cortex to the learning process.

The importance of decision onset

The neural mechanisms of decision making are thought to require the integration of evidence over time until a response threshold is reached. Much work suggests that response threshold can be adjusted via top-down control as a function of speed or accuracy requirements. In contrast, the time of integration onset has received less attention and is believed to be determined mostly by afferent or preprocessing delays. However, a number of influential studies over the past decade challenge this assumption and begin to paint a multifaceted view of the phenomenology of decision onset. This review highlights the challenges involved in initiating the integration of evidence at the optimal time and the potential benefits of adjusting integration onset to task demands. The review outlines behavioral and electrophysiolgical studies suggesting that the onset of the integration process may depend on properties of the stimulus, the task, attention, and response strategy. Most importantly, the aggregate findings in the literature suggest that integration onset may be amenable to top-down regulation, and may be adjusted much like response threshold to exert cognitive control and strategically optimize the decision process to fit immediate behavioral requirements.

Reconsidering Visual Search

The visual search paradigm has had an enormous impact in many fields. A theme running through this literature has been the distinction between preattentive and attentive processing, which I refer to as the two-stage assumption. Under this assumption, slopes of set-size and response time are used to determine whether attention is needed for a given task or not. Even though a lot of findings question this two-stage assumption, it still has enormous influence, determining decisions on whether papers are published or research funded. The results described here show that the two-stage assumption leads to very different conclusions about the operation of attention for identical search tasks based only on changes in response (presence/absence versus Go/No-go responses). Slopes are therefore an ambiguous measure of attentional involvement. Overall, the results suggest that the two-stage model cannot explain all findings on visual search, and they highlight how slopes of response time and set-size should only be used with caution.

Patient load effects on response time to critical arrhythmias in cardiac telemetry: a randomized trial

OBJECTIVES

Remotely monitored patients may be at risk for a delayed response to critical arrhythmias if the telemetry watchers who monitor them are subject to an excessive patient load. There are no guidelines or studies regarding the appropriate number of patients that a single watcher may safely and effectively monitor. Our objective was to determine the impact of increasing the number of patients monitored on response time to simulated cardiac arrest.

DESIGN

Randomized trial.

SETTING

Laboratory-based experiment.

SUBJECTS

Forty-two remote telemetry technicians and nurses from cardiac units.

INTERVENTIONS

Number of patients monitored in a simulation of cardiac telemetry monitoring work.

MEASUREMENTS AND MAIN RESULTS

We carried out a study to compare response times to ventricular fibrillation across five patient loads: 16, 24, 32, 40, and 48 patients. The simulation replicated the work of telemetry watchers using a combination of real recorded patient electrocardiogram signals and a simulated patient experiencing ventricular fibrillation. Study participants were assigned to one of the five patient loads and completed a 4-hour monitoring session, during which they performed tasks-including event documentation and phone calls to report events-similar to real monitoring work. When the simulated patient sustained ventricular fibrillation, the time required to report this arrhythmia was recorded. As patient loads increased, there was a statistically significant increase in response times to the ventricular fibrillation. In addition, frequency of failure to meet a response time goal of less than 20 seconds was significantly higher in the 48-patient condition than in all other conditions. Task performance decreased as patient load increased.

CONCLUSIONS

As participants monitored more patients in a laboratory setting, their performance with respect to recognizing critical and noncritical events declined. This study has implications for the design of remote telemetry work and other patient monitoring tasks in critical and intermediate care units.

Different target-discrimination times can be followed by the same saccade-initiation timing in different stimulus conditions during visual searches

The neuronal processes that underlie visual searches can be divided into two stages: target discrimination and saccade preparation/generation. This predicts that the length of time of the prediscrimination stage varies according to the search difficulty across different stimulus conditions, whereas the length of the latter postdiscrimination stage is stimulus invariant. However, recent studies have suggested that the length of the postdiscrimination interval changes with different stimulus conditions. To address whether and how the visual stimulus affects determination of the postdiscrimination interval, we recorded single-neuron activity in the lateral intraparietal area (LIP) when monkeys (Macaca fuscata) performed a color-singleton search involving four stimulus conditions that differed regarding luminance (Bright vs. Dim) and target-distractor color similarity (Easy vs. Difficult). We specifically focused on comparing activities between the Bright-Difficult and Dim-Easy conditions, in which the visual stimuli were considerably different, but the mean reaction times were indistinguishable. This allowed us to examine the neuronal activity when the difference in the degree of search speed between different stimulus conditions was minimal. We found that not only prediscrimination but also postdiscrimination intervals varied across stimulus conditions: the postdiscrimination interval was longer in the Dim-Easy condition than in the Bright-Difficult condition. Further analysis revealed that the postdiscrimination interval might vary with stimulus luminance. A computer simulation using an accumulation-to-threshold model suggested that the luminance-related difference in visual response strength at discrimination time could be the cause of different postdiscrimination intervals.

The what, where, and why of priority maps and their interactions with visual working memory

Priority maps are winner-take-all neural mechanisms thought to guide the allocation of covert and overt attention. Here, we go beyond this standard definition and argue that priority maps play a much broader role in controlling goal-directed behavior. We start by defining what priority maps are and where they might be found in the brain; we then ask why they exist-the function that they serve. We propose that this function is to communicate a goal state to the different effector systems, thereby guiding behavior. Within this framework, we speculate on how priority maps interact with visual working memory and introduce our common source hypothesis, the suggestion that this goal state is maintained in visual working memory and used to construct all of the priority maps controlling the various motor systems. Finally, we look ahead and suggest questions about priority maps that should be asked next.

Decoupling speed and accuracy in an urgent decision-making task reveals multiple contributions to their trade-off

A key goal in the study of decision making is determining how neural networks involved in perception and motor planning interact to generate a given choice, but this is complicated due to the internal trade-off between speed and accuracy, which confounds their individual contributions. Urgent decisions, however, are special: they may range between random and fully informed, depending on the amount of processing time (or stimulus viewing time) available in each trial, but regardless, movement preparation always starts early on. As a consequence, under time pressure it is possible to produce a psychophysical curve that characterizes perceptual performance independently of reaction time, and this, in turn, makes it possible to pinpoint how perceptual information (which requires sensory input) modulates motor planning (which does not) to guide a choice. Here we review experiments in which, on the basis of this approach, the origin of the speed-accuracy trade-off becomes particularly transparent. Psychophysical, neurophysiological, and modeling results in the "compelled-saccade" task indicate that, during urgent decision making, perceptual information-if and whenever it becomes available-accelerates or decelerates competing motor plans that are already ongoing. This interaction affects both the reaction time and the probability of success in any given trial. In two experiments with reward asymmetries, we find that speed and accuracy can be traded in different amounts and for different reasons, depending on how the particular task contingencies affect specific neural mechanisms related to perception and motor planning. Therefore, from the vantage point of urgent decisions, the speed-accuracy trade-off is not a unique phenomenon tied to a single underlying mechanism, but rather a typical outcome of many possible combinations of internal adjustments within sensory-motor neural circuits.

Lateralized readiness potentials reveal properties of a neural mechanism for implementing a decision threshold

Many perceptual decision making models posit that participants accumulate noisy evidence over time to improve the accuracy of their decisions, and that in free response tasks, participants respond when the accumulated evidence reaches a decision threshold. Research on the neural correlates of these models' components focuses primarily on evidence accumulation. Far less attention has been paid to the neural correlates of decision thresholds, reflecting the final commitment to a decision. Inspired by a model of bistable neural activity that implements a decision threshold, we reinterpret human lateralized readiness potentials (LRPs) as reflecting the crossing of a decision threshold. Interestingly, this threshold crossing preserves signatures of a drift-diffusion process of evidence accumulation that feeds in to the threshold mechanism. We show that, as our model predicts, LRP amplitudes and growth rates recorded while participants performed a motion discrimination task correlate with individual differences in behaviorally-estimated prior beliefs, decision thresholds and evidence accumulation rates. As such LRPs provide a useful measure to test dynamical models of both evidence accumulation and decision commitment processes non-invasively.

Extrafoveal preview benefit during free-viewing visual search in the monkey

Previous studies have shown that subjects require less time to process a stimulus at the fovea after a saccade if they have viewed the same stimulus in the periphery immediately prior to the saccade. This extrafoveal preview benefit indicates that information about the visual form of an extrafoveally viewed stimulus can be transferred across a saccade. Here, we extend these findings by demonstrating and characterizing a similar extrafoveal preview benefit in monkeys during a free-viewing visual search task. We trained two monkeys to report the orientation of a target among distractors by releasing one of two bars with their hand; monkeys were free to move their eyes during the task. Both monkeys took less time to indicate the orientation of the target after foveating it, when the target lay closer to the fovea during the previous fixation. An extrafoveal preview benefit emerged even if there was more than one intervening saccade between the preview and the target fixation, indicating that information about target identity could be transferred across more than one saccade and could be obtained even if the search target was not the goal of the next saccade. An extrafoveal preview benefit was also found for distractor stimuli. These results aid future physiological investigations of the extrafoveal preview benefit.

Perceptual modulation of motor--but not visual--responses in the frontal eye field during an urgent-decision task

Neuronal activity in the frontal eye field (FEF) ranges from purely motor (related to saccade production) to purely visual (related to stimulus presence). According to numerous studies, visual responses correlate strongly with early perceptual analysis of the visual scene, including the deployment of spatial attention, whereas motor responses do not. Thus, functionally, the consensus is that visually responsive FEF neurons select a target among visible objects, whereas motor-related neurons plan specific eye movements based on such earlier target selection. However, these conclusions are based on behavioral tasks that themselves promote a serial arrangement of perceptual analysis followed by motor planning. So, is the presumed functional hierarchy in FEF an intrinsic property of its circuitry or does it reflect just one possible mode of operation? We investigate this in monkeys performing a rapid-choice task in which, crucially, motor planning always starts ahead of task-critical perceptual analysis, and the two relevant spatial locations are equally informative and equally likely to be target or distracter. We find that the choice is instantiated in FEF as a competition between oculomotor plans, in agreement with model predictions. Notably, although perception strongly influences the motor neurons, it has little if any measurable impact on the visual cells; more generally, the more dominant the visual response, the weaker the perceptual modulation. The results indicate that, contrary to expectations, during rapid saccadic choices perceptual information may directly modulate ongoing saccadic plans, and this process is not contingent on prior selection of the saccadic goal by visually driven FEF responses.

Parietal blood oxygenation level-dependent response evoked by covert visual search reflects set-size effect in monkeys

Distinguishing a target from distractors during visual search is crucial for goal-directed behaviour. The more distractors that are presented with the target, the larger is the subject's error rate. This observation defines the set-size effect in visual search. Neurons in areas related to attention and eye movements, like the lateral intraparietal area (LIP) and frontal eye field (FEF), diminish their firing rates when the number of distractors increases, in line with the behavioural set-size effect. Furthermore, human imaging studies that have tried to delineate cortical areas modulating their blood oxygenation level-dependent (BOLD) response with set size have yielded contradictory results. In order to test whether BOLD imaging of the rhesus monkey cortex yields results consistent with the electrophysiological findings and, moreover, to clarify if additional other cortical regions beyond the two hitherto implicated are involved in this process, we studied monkeys while performing a covert visual search task. When varying the number of distractors in the search task, we observed a monotonic increase in error rates when search time was kept constant as was expected if monkeys resorted to a serial search strategy. Visual search consistently evoked robust BOLD activity in the monkey FEF and a region in the intraparietal sulcus in its lateral and middle part, probably involving area LIP. Whereas the BOLD response in the FEF did not depend on set size, the LIP signal increased in parallel with set size. These results demonstrate the virtue of BOLD imaging in monkeys when trying to delineate cortical areas underlying a cognitive process like visual search. However, they also demonstrate the caution needed when inferring neural activity from BOLD activity.

Production, control, and visual guidance of saccadic eye movements

Primate vision is served by rapid shifts of gaze called saccades. This review will survey current knowledge and particular problems concerning the neural control and guidance of gaze shifts.

Neural chronometry and coherency across speed-accuracy demands reveal lack of homomorphism between computational and neural mechanisms of evidence accumulation

The stochastic accumulation framework provides a mechanistic, quantitative account of perceptual decision-making and how task performance changes with experimental manipulations. Importantly, it provides an elegant account of the speed-accuracy trade-off (SAT), which has long been the litmus test for decision models, and also mimics the activity of single neurons in several key respects. Recently, we developed a paradigm whereby macaque monkeys trade speed for accuracy on cue during visual search task. Single-unit activity in frontal eye field (FEF) was not homomorphic with the architecture of models, demonstrating that stochastic accumulators are an incomplete description of neural activity under SAT. This paper summarizes and extends this work, further demonstrating that the SAT leads to extensive, widespread changes in brain activity never before predicted. We will begin by reviewing our recently published work that establishes how spiking activity in FEF accomplishes SAT. Next, we provide two important extensions of this work. First, we report a new chronometric analysis suggesting that increases in perceptual gain with speed stress are evident in FEF synaptic input, implicating afferent sensory-processing sources. Second, we report a new analysis demonstrating selective influence of SAT on frequency coupling between FEF neurons and local field potentials. None of these observations correspond to the mechanics of current accumulator models.

On the origin of event-related potentials indexing covert attentional selection during visual search: timing of selection by macaque frontal eye field and event-related potentials during pop-out search

Event-related potentials (ERPs) have provided crucial data concerning the time course of psychological processes, but the neural mechanisms producing ERP components remain poorly understood. This study continues a program of research in which we investigated the neural basis of attention-related ERP components by simultaneously recording intracranially and extracranially from macaque monkeys. Here, we compare the timing of attentional selection by the macaque homologue of the human N2pc component (m-N2pc) with the timing of selection in the frontal eye field (FEF), an attentional-control structure believed to influence posterior visual areas thought to generate the N2pc. We recorded FEF single-unit spiking and local field potentials (LFPs) simultaneously with the m-N2pc in monkeys performing an efficient pop-out search task. We assessed how the timing of attentional selection depends on task demands by direct comparison with a previous study of inefficient search in the same monkeys (e.g., finding a T among Ls). Target selection by FEF spikes, LFPs, and the m-N2pc was earlier during efficient pop-out search rather than during inefficient search. The timing and magnitude of selection in all three signals varied with set size during inefficient but not efficient search. During pop-out search, attentional selection was evident in FEF spiking and LFP before the m-N2pc, following the same sequence observed during inefficient search. These observations are consistent with the hypothesis that feedback from FEF modulates neural activity in posterior regions that appear to generate the m-N2pc even when competition for attention among items in a visual scene is minimal.

Visual response of neurons in the lateral intraparietal area and saccadic reaction time during a visual detection task

During visual detection with saccades, a target with higher luminance is detected with reduced reaction times. In such visual detection behaviors, luminance-related sensory signals should be converted into movement-related signals for saccade initiation. At the site where the visuomotor transformation takes place, there is the possibility that visual activity not only encodes the target luminance but also affects the generation of an upcoming saccade. To assess this possibility, we recorded single-cell activity from visually responsive neurons in the lateral intraparietal area (LIP) when monkeys made a saccade to an isolated target over five luminance levels. We found that as stimulus luminance increased, visual response strength increased, and response onset latency decreased. These luminance-related changes in activity were significantly correlated with changes in reaction time. In particular, changes in response onset latency accounted for a substantial part of the observed changes in reaction time, suggesting that luminance-related changes in response onset latency may propagate to the saccade generation process. However, the length of time from response onset to saccade onset was not constant but increased as luminance was reduced, suggesting the existence of other luminance-dependent processing in downstream and/or parallel pathways before saccade generation. Additionally, we failed to find strong covariance between response strength or latency and reaction time when the effect of luminance changes was removed. Thus, the present results reveal how visually responsive LIP neurons contribute to saccade generation in visual detection.

Response variability of frontal eye field neurons modulates with sensory input and saccade preparation but not visual search salience

Discharge rate modulation of frontal eye field (FEF) neurons has been identified with a representation of visual search salience (physical conspicuity and behavioral relevance) and saccade preparation. We tested whether salience or saccade preparation are evident in the trial-to-trial variability of discharge rate. We quantified response variability via the Fano factor in FEF neurons recorded in monkeys performing efficient and inefficient visual search tasks. Response variability declined following stimulus presentation in most neurons, but despite clear discharge rate modulation, variability did not change with target salience. Instead, we found that response variability was modulated by stimulus luminance and the number of items in the visual field independently of attentional demands. Response variability declined to a minimum before saccade initiation, and presaccadic response variability was directionally tuned. In addition, response variability was correlated with the response time of memory-guided saccades. These results indicate that the trial-by-trial response variability of FEF neurons reflects saccade preparation and the strength of sensory input, but not visual search salience or attentional allocation.

Frontoparietal theta activity supports behavioral decisions in movement-target selection

There is recent EEG evidence describing task-related changes of theta power in spatial attention and reaching/pointing tasks. Here, we aim to better characterize this theta activity and determine whether it is associated with visuospatial memory or with visuospatial selection functions of the frontoparietal cortex. We recorded EEG from 20 participants during a movement precuing task with center-out joystick movements. Precues displayed 1, 2, or 4 potential targets and were followed (stimulus onset asynchrony 1.2 s) by a central response cue indicating the movement-target. Remembering the precued target location(s) was mandatory in one and optional in a second version of the task. Analyses evaluated two slow brain potentials (CNV, contingent negative variation and CDA, contralateral delay activity) and task-related power changes. Results showed a differential modulation of frontal CNV and parietal CDA, consistent with earlier described set-size effects on motor preparation and visual short-term memory. Short-lived phases of theta event-related synchronization (ERS) were found 150-500 ms after precue and response cue presentation, exhibiting parietal and frontal maxima. The increase of frontoparietal theta power following response cue presentation was strongly modulated by target load, i.e., absent for 1-target (when the movement-target could be selected in advance), contrasting with a robust 20-50% ERS response in 2- and 4-target conditions. The scalp distribution, the timing, and the modulation by set-size suggest a role of theta activity in movement-target selection. The results support a recently proposed view of theta as emerging around behavioral decision points, linked to the evaluation of choice-relevant information.

New advances in understanding decisions among multiple alternatives

Experimental studies of decision-making have put a strong emphasis on choices between two alternatives. However, real-life decisions often involve multiple alternatives. This article provides an overview of theoretical frameworks that have been proposed to account for behavioral data from both economic and perceptual multialternative decision-making. We further review recent neurophysiological data collected in conjunction with decision-making behavior. These neural recordings provide constraints on putative models of the decision mechanism. For example, the time course of inhibition provides insight into how the competition between alternatives is mediated. Furthermore, whereas decision-related neural activity seems to reach a common threshold at the end of the decision period, the starting point tends to depend systematically on the number of alternatives. We discuss candidate mechanisms that could drive the reduction in firing rates on decisions among multiple alternatives.

From salience to saccades: multiple-alternative gated stochastic accumulator model of visual search

We describe a stochastic accumulator model demonstrating that visual search performance can be understood as a gated feedforward cascade from a salience map to multiple competing accumulators. The model quantitatively accounts for behavior and predicts neural dynamics of macaque monkeys performing visual search for a target stimulus among different numbers of distractors. The salience accumulated in the model is equated with the spike trains recorded from visually responsive neurons in the frontal eye field. Accumulated variability in the firing rates of these neurons explains choice probabilities and the distributions of correct and error response times with search arrays of different set sizes if the accumulators are mutually inhibitory. The dynamics of the stochastic accumulators quantitatively predict the activity of presaccadic movement neurons that initiate eye movements if gating inhibition prevents accumulation before the representation of stimulus salience emerges. Adjustments in the level of gating inhibition can control trade-offs in speed and accuracy that optimize visual search performance.

Neural mechanisms of saccade target selection: gated accumulator model of the visual-motor cascade

We review a new computational model developed to understand how evidence about stimulus salience in visual search is translated into a saccade command. The model uses the activity of visually responsive neurons in the frontal eye field as evidence for stimulus salience that is accumulated in a network of stochastic accumulators to produce accurate and timely saccades. We discovered that only when the input to the accumulation process was gated could the model account for the variability in search performance and predict the dynamics of movement neuron discharge rates. This union of cognitive modeling and neurophysiology indicates how the visual-motor transformation can occur, and provides a concrete mapping between neuron function and specific cognitive processes.

The search for the neural mechanisms of the set size effect

The set size effect in visual search refers to the linear increase in response time (RT) or decrease in accuracy as the number of distractors increases. Previous human and monkey studies have reported a correlation between set size and neural activity in the frontal eye field (FEF) and intraparietal sulcus (IPS). In a recent functional magnetic resonance imaging study, we did not observe a set size effect in the superior precentral sulcus (sPCS, thought to be the human homolog of the FEF) and IPS in an oculomotor visual search task (Ikkai et al., 2011). Our task used placeholders in the search array, along with the target and distractors, in order to equate the amount of retinal stimulation for each set size. We here attempted to reconcile these differences with the results from a follow-up experiment in which the same oculomotor visual search task was used, but without placeholders. A strong behavioral set size effect was observed in both studies, with very similar saccadic RTs and slopes between RT and set size. However, a set size effect was now observed in the sPCS and IPS. We comment on this finding and discuss the role of these neural areas in visual search.

Spatial interactions in the superior colliculus predict saccade behavior in a neural field model

During natural vision, eye movements are dynamically controlled by the combinations of goal-related top-down (TD) and stimulus-related bottom-up (BU) neural signals that map onto objects or locations of interest in the visual world. In primates, both BU and TD signals converge in many areas of the brain, including the intermediate layers of the superior colliculus (SCi), a midbrain structure that contains a retinotopically coded map for saccades. How TD and BU signals combine or interact within the SCi map to influence saccades remains poorly understood and actively debated. It has been proposed that winner-take-all competition between these signals occurs dynamically within this map to determine the next location for gaze. Here, we examine how TD and BU signals interact spatially within an artificial two-dimensional dynamic winner-take-all neural field model of the SCi to influence saccadic RT (SRT). We measured point images (spatially organized population activity on the SC map) physiologically to inform the TD and BU model parameters. In this model, TD and BU signals interacted nonlinearly within the SCi map to influence SRT via changes to the (1) spatial size or extent of individual signals, (2) peak magnitude of individual signals, (3) total number of competing signals, and (4) the total spatial separation between signals in the visual field. This model reproduced previous behavioral studies of TD and BU influences on SRT and accounted for multiple inconsistencies between them. This is achieved by demonstrating how, under different experimental conditions, the spatial interactions of TD and BU signals can lead to either increases or decreases in SRT. Our results suggest that dynamic winner-take-all modeling with local excitation and distal inhibition in two dimensions accurately reflects both the physiological activity within the SCi map and the behavioral changes in SRT that result from BU and TD manipulations.

Neural correlates of perceptual decision making before, during, and after decision commitment in monkey frontal eye field

Perceptual decision making requires a complex set of computations to implement, evaluate, and adjust the conversion of sensory input into a categorical judgment. Little is known about how the specific underlying computations are distributed across and within different brain regions. Using a reaction-time (RT) motion direction-discrimination task, we show that a unique combination of decision-related signals is represented in monkey frontal eye field (FEF). Some responses were modulated by choice, motion strength, and RT, consistent with a temporal accumulation of sensory evidence. These responses converged to a threshold level prior to behavioral responses, reflecting decision commitment. Other responses continued to be modulated by motion strength even after decision commitment, possibly providing a memory trace to help evaluate and adjust the decision process with respect to rewarding outcomes. Both response types were encoded by FEF neurons with both narrow- and broad-spike waveforms, presumably corresponding to inhibitory interneurons and excitatory pyramidal neurons, respectively, and with diverse visual, visuomotor, and motor properties, albeit with different frequencies. Thus, neurons throughout FEF appear to make multiple contributions to decision making that only partially overlap with contributions from other brain regions. These results help to constrain how networks of brain regions interact to generate perceptual decisions.

Modulation of shifting receptive field activity in frontal eye field by visual salience

In the monkey frontal eye field (FEF), the sensitivity of some neurons to visual stimulation changes just before a saccade. Sensitivity shifts from the spatial location of its current receptive field (RF) to the location of that field after the saccade is completed (the future field, FF). These shifting RFs are thought to contribute to the stability of visual perception across saccades, and in this study we investigated whether the salience of the FF stimulus alters the magnitude of FF activity. We reduced the salience of the usually single flashed stimulus by adding other visual stimuli. We isolated 171 neurons in the FEF of 2 monkeys and did experiments on 50 that had FF activity. In 30% of these, that activity was higher before salience was reduced by adding stimuli. The mean magnitude reduction was 16%. We then determined whether the shifting RFs were more frequent in the central visual field, which would be expected if vision across saccades were only stabilized for the visual field near the fovea. We found no evidence of any skewing of the frequency of shifting receptive fields (or the effects of salience) toward the central visual field. We conclude that the salience of the FF stimulus makes a substantial contribution to the magnitude of FF activity in FEF. In so far as FF activity contributes to visual stability, the salience of the stimulus is probably more important than the region of the visual field in which it falls for determining which objects remain perceptually stable across saccades.

Neurally constrained modeling of perceptual decision making

Stochastic accumulator models account for response time in perceptual decision-making tasks by assuming that perceptual evidence accumulates to a threshold. The present investigation mapped the firing rate of frontal eye field (FEF) visual neurons onto perceptual evidence and the firing rate of FEF movement neurons onto evidence accumulation to test alternative models of how evidence is combined in the accumulation process. The models were evaluated on their ability to predict both response time distributions and movement neuron activity observed in monkeys performing a visual search task. Models that assume gating of perceptual evidence to the accumulating units provide the best account of both behavioral and neural data. These results identify discrete stages of processing with anatomically distinct neural populations and rule out several alternative architectures. The results also illustrate the use of neurophysiological data as a model selection tool and establish a novel framework to bridge computational and neural levels of explanation.

Neural correlates of correct and errant attentional selection revealed through N2pc and frontal eye field activity

The goal of this study was to obtain a better understanding of the physiological basis of errors of visual search. Previous research has shown that search errors occur when visual neurons in the frontal eye field (FEF) treat distractors as if they were targets. We replicated this finding during an inefficient form search and extended it by measuring simultaneously a macaque homologue of an event-related potential indexing the allocation of covert attention known as the m-N2pc. Based on recent work, we expected errors of selection in FEF to propagate to areas of extrastriate cortex responsible for allocating attention and implicated in the generation of the m-N2pc. Consistent with this prediction, we discovered that when FEF neurons selected a distractor instead of the search target, the m-N2pc shifted in the same, incorrect direction prior to the erroneous saccade. This suggests that such errors are due to a systematic misorienting of attention from the initial stages of visual processing. Our analyses also revealed distinct neural correlates of false alarms and guesses. These results demonstrate that errant gaze shifts during visual search arise from errant attentional processing.

Perception and action selection dissociate human ventral and dorsal cortex

We test theories about the functional organization of the human cortex by correlating brain activity with demands on perception versus action selection. Subjects covertly searched for a target among an array of 4, 8, or 12 items (perceptual manipulation) and then, depending on the color of the array, made a saccade toward, away from, or at a right angle from the target (action manipulation). First, choice response times increased linearly as the demands increased for each factor, and brain activity in several cortical areas increased with increasing choice response times. Second, we found a double dissociation in posterior cortex: Activity in ventral regions (occipito-temporal cortex) increased linearly with perceptual, but not action, selection demands; conversely, activity in dorsal regions (parietal cortex) increased linearly with action, but not perceptual, selection demands. This result provides the clearest support of the theory that posterior cortex is segregated into two distinct streams of visual processing for perception and action. Third, despite segregated anatomical projections from posterior ventral and dorsal streams to lateral pFC, we did not find evidence for a functional dissociation between perception and action selection in pFC. Increasing action, but not perceptual, selection demands evoked increased activation along both the dorsal and the ventral lateral pFC. Although most previous studies have focused on perceptual variables (e.g., space vs. object), these data suggest that understanding the computations underlying action selection will be key to understanding the functional organization of pFC.

Cooperation and competition among frontal eye field neurons during visual target selection

The role of spike rate versus timing codes in visual target selection is unclear. We simultaneously recorded activity from multiple frontal eye field neurons and asked whether they interacted to select targets from distractors during visual search. When both neurons in a pair selected the target and had overlapping receptive fields (RFs), they cooperated more than when one or neither neuron in the pair selected the target, measured by positive spike timing correlations using joint peristimulus time histogram analysis. The amount of cooperation depended on the location of the search target: it was higher when the target was inside both neurons' RFs than when it was inside one RF but not the other, or outside both RFs. Elevated spike timing coincidences occurred at the time of attentional selection of the target as measured by average modulation of discharge rates. We observed competition among neurons with spatially non-overlapping RFs, measured by negative spike timing correlations. Thus, we provide evidence for dynamic and task-dependent cooperation and competition among frontal eye field neurons during visual target selection.

Simultaneous preparation of multiple potential movements: opposing effects of spatial proximity mediated by premotor and parietal cortex

Neurophysiological studies in monkey have suggested that premotor and motor cortex may prepare for multiple movements simultaneously, sustained by cooperative and competitive interactions within and between the neural populations encoding different actions. Here, we investigate whether competition between alternative movement directions, manipulated in terms of number and spatial angle, is reflected in electroencephalographic (EEG) measures of (pre)motor cortical activity in humans. EEG was recorded during performance of a center-out pointing task in which response signals were preceded by cues providing prior information in the form of arrows pointing to one or more possible movement targets. Delay-period activity in (pre)motor cortex was modulated in the predicted manner by the number of possible movement directions and by the angle separating them. Response latencies, however, were determined not only by the amplitude of movement-preparatory activity, but also by differences in the duration of stimulus evaluation against the visuospatial memory of the cue, reflected in EEG potentials originating from posterior parietal cortex (PPC). Specifically, the spatial proximity of possible movement targets was processed differently by (pre)motor and posterior parietal cortex. Spatial proximity enhanced the amplitude of (pre)motor cortex preparatory activity during the delay period but delayed evaluation of the response signal in the PPC, thus producing opposite effects on response latency. The latter finding supports distributed control of movement decisions in the frontoparietal network, revealing a feature of distributed control that is of potential significance for the understanding of distracter effects in reaching and pointing.